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content/.quarto/cites/index.json

@@ -1 +1 @@
-{"1_introduction.qmd":[],"4_1_Normal.qmd":["wagenmakers2008diffusion","theriault2024check","lo2015transform","schramm2019reaction"],"4_rt.qmd":["wagenmakers2008diffusion","theriault2024check","lo2015transform","schramm2019reaction"],"references.qmd":[],"3_scales.qmd":[],"2_predictors.qmd":[],"5_individual.qmd":[],"index.qmd":[]}
+{"index.qmd":[],"1_introduction.qmd":[],"2_predictors.qmd":[],"5_individual.qmd":[],"references.qmd":[],"4_1_Normal.qmd":["wagenmakers2008diffusion","theriault2024check","lo2015transform","schramm2019reaction"],"3_scales.qmd":[],"4_rt.qmd":["wagenmakers2008diffusion","heathcote2012linear","theriault2024check","lo2015transform","schramm2019reaction"]}

content/.quarto/xref/15f266d2

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-{"headings":["very-quick-intro-to-julia-and-turing","generate-data-from-normal-distribution","recover-distribution-parameters-with-turing","linear-models","boostrapping","hierarchical-models","bayesian-estimation","bayesian-mixed-linear-regression"],"entries":[],"options":{"chapters":true}}
+{"entries":[],"headings":["very-quick-intro-to-julia-and-turing","generate-data-from-normal-distribution","recover-distribution-parameters-with-turing","linear-models","boostrapping","hierarchical-models","bayesian-estimation","bayesian-mixed-linear-regression"],"options":{"chapters":true}}

content/.quarto/xref/1a47137c

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-{"headings":[],"entries":[],"options":{"chapters":true}}
+{"options":{"chapters":true},"entries":[],"headings":[]}

content/.quarto/xref/26afb962

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-{"options":{"chapters":true},"headings":["categorical-predictors-condition-group","ordered-predictors-likert-scales","interactions","non-linear-relationships-polynomial-gams"],"entries":[]}
+{"entries":[],"options":{"chapters":true},"headings":["categorical-predictors-condition-group","ordered-predictors-likert-scales","interactions","non-linear-relationships-polynomial-gams"]}

content/.quarto/xref/6cbe9151

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-{"headings":["preface","why-julia","why-bayesian","the-plan","looking-for-coauthors"],"options":{"chapters":true},"entries":[]}
+{"entries":[],"options":{"chapters":true},"headings":["preface","why-julia","why-bayesian","the-plan","looking-for-coauthors"]}

content/.quarto/xref/ce37606d

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-{"entries":[],"headings":[],"options":{"chapters":true}}
+{"headings":[],"entries":[],"options":{"chapters":true}}

content/.quarto/xref/efe17597

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-{"headings":["the-data","descriptive-models","gaussian-aka-linear-model","model-specification","posterior-predictive-check","scaled-gaussian-model","solution-1-directional-effect-of-condition","solution-2-avoid-exploring-negative-variance-values","the-problem-with-linear-models","shifted-lognormal-model","model","more-conditional-parameters","exgaussian-model","wald-model","generative-models-ddm","other-models-lba-lnr","including-random-effects","additional-resources"],"entries":[],"options":{"chapters":true}}
+{"headings":["the-data","descriptive-models","gaussian-aka-linear-model","model-specification","posterior-predictive-check","scaled-gaussian-model","solution-1-directional-effect-of-condition","solution-2-avoid-exploring-negative-variance-values","the-problem-with-linear-models","shifted-lognormal-model","model","more-conditional-parameters","exgaussian-model","wald-model","generative-models-ddm","other-models-lba-lnr","including-random-effects","additional-resources"],"options":{"chapters":true},"entries":[]}

content/4_rt.qmd

@@ -4,8 +4,8 @@
 
 ## The Data
 
-Data from @wagenmakers2008diffusion - Experiment 1.
-Using the same procedure as the authors, we excluded all trials with uninterpretable response time [see @theriault2024check], i.e., responses that are too fast response (<180 ms) or too slow (>2 sec instead of >3 sec).
+For this chapter, we will be using the data from @wagenmakers2008diffusion - Experiment 1 [also reanalyzed by @heathcote2012linear], that contains responses and response times for several participants in two conditions (where instructions emphasized either **speed** or **accuracy**).
+Using the same procedure as the authors, we excluded all trials with uninterpretable response time, i.e., responses that are too fast (<180 ms) or too slow [>2 sec instead of >3 sec, see @theriault2024check for a discussion on outlier removal].
 
 ```{julia}
 #| code-fold: false

content/references.bib

@@ -27,6 +27,16 @@ @article{lo2015transform
   publisher={Frontiers Media SA}
 }
 
+@article{heathcote2012linear,
+  title={Linear deterministic accumulator models of simple choice},
+  author={Heathcote, Andrew and Love, Jonathon},
+  journal={Frontiers in psychology},
+  volume={3},
+  pages={292},
+  year={2012},
+  publisher={Frontiers Research Foundation}
+}
+
 @article{wagenmakers2008diffusion,
   title={A diffusion model account of criterion shifts in the lexical decision task},
   author={Wagenmakers, Eric-Jan and Ratcliff, Roger and Gomez, Pablo and McKoon, Gail},